class_docstr: Iterator yielding data from a Numpy array.
  
  # Arguments
      x: Numpy array of input data or tuple.
          If tuple, the second elements is either
          another numpy array or a list of numpy arrays,
          each of which gets passed
          through as an output without any modifications.
      y: Numpy array of targets data.
      image_data_generator: Instance of `ImageDataGenerator`
          to use for random transformations and normalization.
      batch_size: Integer, size of a batch.
      shuffle: Boolean, whether to shuffle the data between epochs.
      sample_weight: Numpy array of sample weights.
      seed: Random seed for data shuffling.
      data_format: String, one of `channels_first`, `channels_last`.
      save_to_dir: Optional directory where to save the pictures
          being yielded, in a viewable format. This is useful
          for visualizing the random transformations being
          applied, for debugging purposes.
      save_prefix: String prefix to use for saving sample
          images (if `save_to_dir` is set).
      save_format: Format to use for saving sample images
          (if `save_to_dir` is set).
      subset: Subset of data (`"training"` or `"validation"`) if
          validation_split is set in ImageDataGenerator.
      ignore_class_split: Boolean (default: False), ignore difference
              in number of classes in labels across train and validation
              split (useful for non-classification tasks)
      dtype: Dtype to use for the generated arrays.
code: def __new__(cls, *args, **kwargs):
      try:
          from tensorflow.keras.utils import Sequence as TFSequence
  
          if TFSequence not in cls.__bases__:
              cls.__bases__ = cls.__bases__ + (TFSequence,)
      except ImportError:
          pass
      return super(NumpyArrayIterator, cls).__new__(cls)
  
file_path: keras-preprocessing/keras_preprocessing/image/numpy_array_iterator.py
imports: import os
  import warnings
  import numpy
  from .iterator import Iterator
  from .utils import array_to_img
label_desc: Use image node_id 1 for calling the NumpyArrayIterator obj's underlying member method code with example usage: obj.__new__(cls) and returns: super